Optimized disaster-recovery-as-a-service system

ABSTRACT

Methods, computer program products, and systems are presented. The methods include, for instance: analyzing a dataset associated with a service provided by the data protection service provider in order to determine a policy for when and how to replicate the respective components of the dataset corresponding to the service from a source site to a target site, such that the target site may perform the service with a minimum cost.

TECHNICAL FIELD

The present disclosure relates to data protection and redundancyservice, and more particularly to methods, computer program products,and systems for optimized Disaster-Recovery-as-a-Service (DRaaS) systemby use of selective data transfer.

BACKGROUND

A data center is a facility that centralizes IT operations and equipmentof an organization to store, to manage and to service data within theorganization, and/or users outside of the organization. Because datacenters are critical in modern IT environment, users of data centersdemand reliable operations and continuous data accessibility from thedata centers in all circumstances. Consequently, most data centers putefforts to fail-safe their facilities at reasonable cost, and dataprotection services are commercially available for such data centers.

SUMMARY

The shortcomings of the prior art are overcome, and additionaladvantages are provided, through the provision, in one aspect, of amethod. The method for optimizing a data protection service providerincludes: analyzing, by the data protection service provider running ona computer of a target site, a first dataset associated with a firstservice provided by the data protection service provider, the firstdataset including components from client data of a source site, suchthat the data protection service provider determines a policycorresponding to the first service, the policy dictating when and how toreplicate the respective components of the first dataset from the sourcesite to the target site in order to minimize cost of providing the firstservice for the source site, wherein the cost includes network bandwidthand storage footprint, the network bandwidth being to replicate thefirst dataset from the source site to the target site, and the storagefootprint being to maintain the first dataset in the target site.

Additional features are realized through the techniques set forthherein. Other embodiments and aspects, including but not limited tocomputer program product and system, are described in detail herein andare considered a part of the claimed invention.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more aspects of the present invention are particularly pointedout and distinctly claimed as examples in the claims at the conclusionof the specification. The foregoing and other objects, features, andadvantages of the invention are apparent from the following detaileddescription taken in conjunction with the accompanying drawings inwhich:

FIG. 1 depicts an optimized Disaster-Recovery-as-a-Service (DRaaS)system by use of selective data transfer, in accordance with one or moreembodiments set forth herein;

FIG. 2 depicts a flowchart for the DRaaS service provider of theoptimized DRaaS system, in accordance with one or more embodiments setforth herein;

FIG. 3 depicts a cloud computing node according to an embodiment of thepresent invention;

FIG. 4 depicts a cloud computing environment according to an embodimentof the present invention; and

FIG. 5 depicts abstraction model layers provided by cloud computingenvironment according to an embodiment of the present invention.

DETAILED DESCRIPTION

FIG. 1 depicts an optimized Disaster-Recovery-as-a-Service (DRaaS)system 100 by use of selective data transfer, in accordance with one ormore embodiments set forth herein.

The optimized DRaaS system 100 includes a client data center 110 and aDisaster-Recovery-as-a-Service (DRaaS) service provider 190. The clientdata center 110 is a data center of a client that provides IT operationand data services to end users, privately within an organization and/orpublicly over a public network. In this specification, term “sourcesite” is used to indicate that the client data center 110 originatesclient data subject to a data protection and other services as providedby the DRaaS service provider 190. The term source site may be usedinterchangeably with term “source zone”, in contrast with terms “targetsite” or “landing zone” indicating the DRaaS service provider 190.

The client data center 110 includes a root disk 113, a data disk 115, adatabase virtual machine (DB VM) 117, and a DRaaS client agent 119. Inone embodiment of the present invention, the DRaaS client agent 119running in the client data center 110 records changes of the client dataon the root disk 113 and the data disk 115 to be duplicated on the DRaaSservice provider 190 for continuous data protection. The changes of theclient data results from input/output requests and disk file changes onthe root disk 113 and the data disk 115, as the client data center 110services end users. In another embodiment of the present invention, theDRaaS client agent 119 interacts with the client to collect informationon which value-added services are selected by the client to be servicedon the target site by the DRaaS service provider 190, as well as ademand by the client for data protection in preparation for a specificoccasion, such as an impending storm.

The DRaaS service provider 190 is a remote data center referred to as atarget site that is distinctive from the client data center 110. TheDRaaS service provider 190 includes a value-added service selectionmodule 120, an essentialness assessment module 130, a policyconfiguration module 140, a DRaaS execution module 150, and a replica180. The DRaaS service provider 190 optimizes traditional disasterrecovery service by analyzing the client data and selectivelytransferring the client data to the target site based on the analysis.The DRaaS service provider 190 also provides one or more value-addedservice as selected by the client.

The DRaaS service provider 190 provides DRaaS services includingcontinuous/on-demand data protection service as well as value-addedservices according to requests of a client operating the client datacenter 110. To provide a data protection service to the client, theDRaaS service provider 190 replicates components of the client datacenter 110 as set forth herein and maintains the replica 180 in theDRaaS service provider 190. The DRaaS service provider 190 minimizes theamount of data to be transferred from the client data center 110 by useof the value-added service selection module 120, the essentialnessassessment module 130, and the policy configuration module 140 such thatthe DRaaS service provider 190 reduces cost on network bandwidth fortransferring the client data to the target site as well as cost onstorage footprint to maintain the client data at the target site.Minimal data transfer is particularly beneficial when the target siteservices numerous clients with very large volumes of data to beprotected, wherein resource of the target site is a bottleneck.

The value-added service selection module 120 enables the client toselect, via the DRaaS client agent 119, from a group of value-addedservices provided by the DRaaS service provider 190, a service that maybe performed on the replica 180 to benefit the client data center 110.Term “value-added service” is used to indicate a service additional todisaster recovery test and/or restoration, which is provided by theDRaaS service provider 190. Examples of value-added services may be, butare not limited to, virus scan, eDiscovery, compressibility estimation,etc.

A dataset of the client data center 110 to be duplicated into thereplica 180 may be determined based on a type of value-added service asselected by the client. For example, the DRaaS service provider 190 mayprovide a virus scanning service on the replica 180 by creating avirtual environment identical to the client data center 110 on the DRaaSservice provider 190, attaching the replica 180, and running ananti-virus software. Because the client may save computational cost toperform the virus scan and a license fee for the anti-virus software,the client data center 110 benefits from choosing to have the DRaaSservice provider 190 virus scan the replica 180. Further examples ofvalue-added services may include, but are not limited to, growth rateestimation, anomaly detection, and compressibility estimation, etc.

The essentialness assessment module 130 analyzes IT characteristics ofcomponents 113, 115, and 117 of the client data center 110 and assessesthe degree of essentialness, represented by an “essentialness score”, ofeach component prior to transfer to the target site. Examples of ITcomponents in the client data center 110 may be, but are not limited to,virtual machines, storage volumes, application programs, etc.

The policy configuration module 140 facilitates the client and/or anadministrator of the DRaaS service provider 190 to configure how toadminister the data protection and value-added services such as when totransfer which data to the target site, according to respectiveessentialness score of components 113, 115, and 117 of the client datacenter 110.

The DRaaS execution module 150 performs the data protection servicesaccording to a backup policy set by the policy configuration module 140.The protection may be a continuous process or a batch process on-demandtriggered by a forecasted disastrous event, a request from the client,etc.

The replica 180 includes only portion of the IT component from theclient data center 110, as transferred pursuant to the essentialnessscore assessed by the essentialness assessment module 130 and a policyset by the policy configuration module 140.

The DRaaS service provider 190 may simultaneously employ otherconventional optimization techniques to minimize resourceconsumption/cost. For example, in order to further reduce the storagefootprint, the DRaaS service provider 190 may use compression,thin-provisioning, and/or deduplication methods along with the analysisand selective transfer of data. Similarly, in order to further reducenetwork bandwidth usage and time/volume of data transfer, the DRaaSservice provider 190 may also use techniques such as deduplication,compression, optimized network protocols, etc.

FIG. 2 depicts a flowchart for the DRaaS service provider 190 of theoptimized DRaaS system 100 of FIG. 1, in accordance with one or moreembodiments set forth herein.

In block 210, the DRaaS service provider 190 identifies which dataset issubject to disaster recovery service and selected value-added service,hereinafter DR/VA services, if any, provided by the DRaaS serviceprovider 190, by use of the value-added service selection module 120. Asa prerequisite, the DRaaS service provider 190 has information as to theservices selected for the client data center by use of the DRaaS clientagent 119. Then the DRaaS service provider 190 proceeds with block 220.

In block 220, the DRaaS service provider 190 analyzes how the datasetidentified in block 210 is relevant to the respective DR/VA services, byuse of the essentialness assessment module 130 and the policyconfiguration module 140. Then the DRaaS service provider 190 proceedswith block 230.

In one embodiment of the present invention, the database virtual machine(DB VM) 117 of the client data center 110 includes three storage volumesrespectively serve as a data volume, a log volume, and an index volume.Traditional data redundancy/protection solutions duplicate all threevolumes as well as a VM disk data to the target site, by use of asoftware agent such as IBM® Softek. (IBM is a registered trademarks ofInternational Business Machines Corporation, Armonk, N.Y., USA.)Contrastingly, the essentialness assessment module 130 of the DRaaSservice provider 190 takes cost-effectiveness into account and gives theindex volume a very low essentialness score, or classifies the indexvolume as Non-essential, because indices in the index volume may bereconstructed from the data volume and the log volume. As the indexvolume can be reconstructed, the index volume may be transferred in adelayed fashion, or not to be transferred at all and reconstructed usingthe transferred data volume and the log volume when the client demands arecovery service to be performed.

The essentialness score is determined by the relative importance of adataset in context of a specific service selected from the DR/VAservices available from the DRaaS service provider 190. Accordingly,each service of the available DR/VA services has respectiveessentialness definition or a standard for dataset assessment. The sametype of dataset may be essential for one service, but may not beessential for another service. Seen from example above, the index volumeis not essential in context of the disaster recovery service, becausethe index volume may be reconstructed at the target site. The indexvolume is not essential in context of compressibility estimationvalue-added service, because the index volume may not be transferred atall, so the compression ratio of the index volume is not essential. Onthe other hand, the index volume is just as essential as other twovolumes in context of anti-virus scanning value-added service, becausethe actual index volume of the client data center, not a substituteindex volume that had been reconstructed at the target site, needs to bescanned and, accordingly, the index volume needs to be transferred.

In one embodiment of the present invention, the essentialness assessmentmodule 130 assigns an essentialness score to an IT component of theclient data center 110. In other embodiment of the present invention,the essentialness assessment module 130 classifies each IT componentinto a predefined level of essentialness, such as “essential” wherein adataset is necessary for an associated service, “valuable” wherein thedataset may improve efficiency of the associated service if transferredbut the associated service can be performed without the dataset beingtransferred, and “non-essential” wherein the transfer of the datasetdoes not impact the associated service in any way.

The essentialness assessment module 130 may obtains information forassessment from various sources such as human input, existingapplication metadata, best practices from known application patterns,and data requirements specific to respective value-added services, etc.Examples of the human input may be, but are not limited to, manuallabeling by the client, etc. Example of the existing applicationmetadata may be, but are not limited to, data dictionary, etc. Exampleof the best practices from known application patterns may be, but arenot limited to, Apache Hadoop® name node and a quorum of data nodes,etc. (Apache Hadoop is a registered trademark of the Apache SoftwareFoundation.) Example of the data requirements specific to respectivevalue-added services may be, but are not limited to, data requirement ofvirus scan service, data requirement of compressibility estimationservice, etc.

The policy configuration module 140 enables the client and/or theadministrator of the DRaaS service provider 190 to configure and specifybackup policies by use of the essentialness score/classificationassigned to each IT component of the client data center 110, forrespective services. An exemplary policy may be “to replicate essentialcomponents first; to replicate valuable components when there is notraffic on the network; and not to replicate non-essential components”.The policy may be represented in any textual formats such as JavaScriptObject Notation (JSON) and Extensible Markup Language (XML). (JavaScriptis a trademark of Oracle Corporation) The administrator of the DRaaSservice provider 190 and/or the client operating the client data centermay modify, revise, and revoke policies according to needs andcircumstances.

In block 230, the DRaaS service provider 190 detects that the DRaaSservice is enabled by both the client and the administrator of the DRaaSservice provider 190, and accordingly, replicates the dataset from theclient data center to the target site, pursuant to the assessedessentialness score and the configured policy from block 220. Then theDRaaS service provider 190 proceeds with block 240.

In block 240, the DRaaS service provider 190 examines a request from theclient. If the DRaaS service provider 190 determines that the request ismade for a dataset recovery service, then the DRaaS service provider 190proceeds with block 250. If the DRaaS service provider 190 determinesthat the request is made for a value-added service, then the DRaaSservice provider 190 proceeds with block 260.

In block 250, the DRaaS service provider 190 recovers entire source sitedataset by use of the replica 180 and by reconstructing source sitedataset that had not been replicated in block 220. The dataset recoveryservice may be performed to recover from an actual disaster, or to testthe DRaaS service provider 190. Then the DRaaS service provider 190terminates one cycle of its process.

In block 260, the DRaaS service provider 190 performs a value-addedservice requested in block 240. Then the DRaaS service provider 190terminates one cycle of its process.

FIGS. 3-5 depict various aspects of computing, including a computersystem and cloud computing, in accordance with one or more aspects setforth herein.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 3, a schematic of an example of a computersystem/cloud computing node is shown. Cloud computing node 10 is onlyone example of a suitable cloud computing node and is not intended tosuggest any limitation as to the scope of use or functionality ofembodiments of the invention described herein. Regardless, cloudcomputing node 10 is capable of being implemented and/or performing anyof the functionality set forth hereinabove.

In cloud computing node 10 there is a computer system 12, which isoperational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system 12 include, but are not limitedto, personal computer systems, server computer systems, thin clients,thick clients, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

Computer system 12 may be described in the general context of computersystem-executable instructions, such as program modules, being executedby a computer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.Computer system 12 may be practiced in distributed cloud computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed cloudcomputing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

As shown in FIG. 3, computer system 12 in cloud computing node 10 isshown in the form of a general-purpose computing device. The componentsof computer system 12 may include, but are not limited to, one or moreprocessors or processing units 16, a system memory 28, and a bus 18 thatcouples various system components including system memory 28 toprocessor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system 12 typically includes a variety of computer systemreadable media. Such media may be any available media that is accessibleby computer system 12, and it includes both volatile and non-volatilemedia, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of an optimizedDisaster-Recovery-as-a-Service (DRaaS) service provider. Program modules42 generally carry out the functions and/or methodologies of embodimentsof the invention as described herein.

Computer system 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computer system12; and/or any devices (e.g., network card, modem, etc.) that enablecomputer system 12 to communicate with one or more other computingdevices. Such communication can occur via Input/Output (I/O) interfaces22. Still yet, computer system 12 can communicate with one or morenetworks such as a local area network (LAN), a general wide area network(WAN), and/or a public network (e.g., the Internet) via network adapter20. As depicted, network adapter 20 communicates with the othercomponents of computer system 12 via bus 18. It should be understoodthat although not shown, other hardware and/or software components couldbe used in conjunction with computer system 12. Examples, include, butare not limited to: microcode, device drivers, redundant processingunits, external disk drive arrays, RAID systems, tape drives, and dataarchival storage systems, etc.

Referring now to FIG. 4, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 4 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 5, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 4) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 5 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and various processing components of aDisaster-Recovery-as-a-Service (DRaaS) service provider 96 as describedherein.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used herein, thesingular forms “a,” “an,” and “the” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willbe further understood that the terms “comprise” (and any form ofcomprise, such as “comprises” and “comprising”), “have” (and any form ofhave, such as “has” and “having”), “include” (and any form of include,such as “includes” and “including”), and “contain” (and any form ofcontain, such as “contains” and “containing”) are open-ended linkingverbs. As a result, a method or device that “comprises,” “has,”“includes,” or “contains” one or more steps or elements possesses thoseone or more steps or elements, but is not limited to possessing onlythose one or more steps or elements. Likewise, a step of a method or anelement of a device that “comprises,” “has,” “includes,” or “contains”one or more features possesses those one or more features, but is notlimited to possessing only those one or more features. Furthermore, adevice or structure that is configured in a certain way is configured inat least that way, but may also be configured in ways that are notlisted.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below, if any, areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description set forth herein has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the disclosure. Theembodiment was chosen and described in order to best explain theprinciples of one or more aspects set forth herein and the practicalapplication, and to enable others of ordinary skill in the art tounderstand one or more aspects as described herein for variousembodiments with various modifications as are suited to the particularuse contemplated.

What is claimed is:
 1. A method for optimizing a data protection service provider, comprising: analyzing, by the data protection service provider running on a computer of a target site, a first dataset associated with a first service provided by the data protection service provider, the first dataset comprising components from client data of a source site, for respective essentialness of the components of the first dataset; configuring, by the data protection service provider, a policy corresponding to the first service, the policy dictating when to replicate the respective components of the first dataset from the source site to the target site based on the respective essentialness of the components of the first dataset from the analyzing in order to minimize amount of data transfer from the source site to the target site in providing the first service for the client data; replicating, from the source site to the target site, the respective components of the first dataset according to the policy from the analyzing, upon detecting inputs enabling the first service, wherein the first service is a disaster recovery service for a database virtual machine of the source site, wherein the first dataset comprises components of a data volume, a log volume, and an index volume of the database virtual machine, wherein the data volume and the log volume are, from the analyzing, respectively determined to be essential for the disaster recovery service and the policy accordingly dictates that the data protection service provider replicates the data volume and the log volume from the source site to the target site, with a highest priority and most frequently, and wherein the index volume is determined to be valuable for the disaster recovery service and the policy accordingly dictates that the data protection service provider does not replicate the index volume from the source site to the target site when network bandwidth is not available but the data protection service provider reconstructs the index volume by use of a replicated data volume and a replicated log volume at the target site; and performing the disaster recovery service in the target site by use of the replicated data volume, the replicated log volume, and a reconstructed index volume.
 2. The method of claim 1, the analyzing comprising: determining that a first component of the first dataset is essential to the first service based on applying analytics data to the first dataset, wherein the first component being essential indicating that the first component is necessary for the target site to provide the first service, and wherein the policy for the first component that is essential dictates the data protection service provider to replicate the first component with a highest priority amongst all components of the first dataset.
 3. The method of claim 1, the analyzing comprising: determining that a second component of the first dataset is valuable to the first service based on applying analytics data to the first dataset, the second component being valuable indicating that the first service can be provided without replicating the second component to the target site, but efficiency of the first service at the target site would improve if the second component is replicated to the target site instead of being reconstructed from other replicated components of the first dataset, and wherein the policy for the second component that is valuable dictates the data protection service provider to replicate the second component when network bandwidth between the source site and the target site is available.
 4. The method of claim 1, the analyzing comprising: determining that a third component of the first dataset is non-essential to the first service based on applying analytics data to the first dataset, the third component being non-essential indicating that a transfer of the third component does not impact the first service at the target site, and wherein the policy for the third component that is non-essential dictates the data protection service provider not to replicate the third component to the target site.
 5. The method of claim 1, wherein the first service is selected from a group consisting of a disaster recovery service and at least one value-added service available from the data protection service provider as selected by the client, wherein the at least one value-added service comprising a disaster recovery test service, a virus scanning service, an eDiscovery service, a compressibility estimation service.
 6. The method of claim 1, further comprising: obtaining, prior to the analyzing, analytics data associated with the first service, wherein the analytics data associated with the first service includes information used for assessing degrees of essentialness for the respective components of the first dataset in performing the first service.
 7. The method of claim 6, wherein the analytics data associated with the first service is selected from the group consisting of IT characteristics of virtual machines, storage volumes, and application programs involved in rendering the first service for the client data.
 8. The method of claim 6, wherein the analytics data associated with the first service is selected from the group consisting of user inputs, respective metadata for existing application programs, best practice patterns, and respective data requirements specific to each services for the client data.
 9. The method of claim 1, the analyzing comprising: determining that each component of the first dataset has an essentialness score equal to one of {essential, valuable, non-essential} with respect to the first service, wherein a first component of the first dataset being essential indicates that the first component is necessary to provide the first service at the target site, and the policy for any essential component dictates the data protection service provider to replicate the essential component with a highest priority amongst all components of the first dataset, wherein a second component of the first dataset being valuable indicates that the second component can be reconstructed from essential components of the first dataset for the first service but the first service would be more efficient if the second component is replicated to the target site, and the policy for any valuable component dictates the data protection service provider to replicate the valuable component when network bandwidth between the source site and the target site is available, and wherein a third component of the first dataset being non-essential indicates that a transfer of the third component to the target site does not impact the first service at the target site, and the policy for any non-essential component dictates the data protection service provider not to replicate the non-essential component to the target site.
 10. A computer program product comprising: a computer readable storage medium readable by one or more processor and storing instructions for execution by the one or more processor for performing a method for optimizing a data protection service provider, comprising: analyzing, by the data protection service provider running on a computer of a target site, a first dataset associated with a first service provided by the data protection service provider, the first dataset comprising components from client data of a source site, such that the data protection service provider determines a policy corresponding to the first service, the policy dictating when and how to replicate the respective components of the first dataset from the source site to the target site in order to minimize cost of providing the first service for the source site, wherein the cost comprises network bandwidth and storage footprint, the network bandwidth being to replicate the first dataset from the source site to the target site, and the storage footprint being to maintain the first dataset in the target site; replicating, from the source site to the target site, the respective components of the first dataset according to the policy from the analyzing, upon detecting inputs enabling the first service, wherein the first service is a virus scanning service for a database virtual machine of the source site, wherein the first dataset comprises a data volume, a log volume, and an index volume of the database virtual machine, and wherein the data volume, the log volume, and the index volume are, from the analyzing, respectively determined to be essential for the virus scanning service and the policy accordingly dictates that the data protection service provider replicates the data volume, the log volume, and the index volume from the source site to the target site with a highest priority and most frequently; and performing the virus scanning service in the target site by use of the replicated data volume, the replicated log volume, and the replicated index volume.
 11. The computer program product of claim 10, the analyzing comprising: determining that a first component of the first dataset is essential to the first service based on applying analytics data to the first dataset, the first component being essential indicating that the first component is necessary for the target site to provide the first service, such that the policy is determined for the data protection service provider to replicate the first component with a highest priority and most frequently.
 12. The computer program product of claim 10, the analyzing comprising: determining that a second component of the first dataset is valuable to the first service based on applying analytics data to the first dataset, the second component being valuable indicating that the second component is not necessary but helpful for the target site to provide the first service, such that the policy is determined for the data protection service provider to replicate the second component if the network bandwidth is available.
 13. The computer program product of claim 10, the analyzing comprising: determining that a third component of the first dataset is non-essential to the first service based on applying analytics data to the first dataset, the third component being non-essential indicating that the third component does not contribute to the first service when present at the target site, such that the policy is determined for the data protection service provider not to replicate the third component to the target site.
 14. A system comprising: a memory; one or more processor in communication with the memory; and program instructions executable by the one or more processor via the memory to perform a method for optimizing a data protection service provider, comprising: analyzing, by the data protection service provider running on a computer of a target site, a first dataset associated with a first service provided by the data protection service provider, the first dataset comprising components from client data of a source site, such that the data protection service provider determines a policy corresponding to the first service, the policy dictating when and how to replicate the respective components of the first dataset from the source site to the target site in order to minimize cost of providing the first service for the source site, wherein the cost comprises network bandwidth and storage footprint, the network bandwidth being to replicate the first dataset from the source site to the target site, and the storage footprint being to maintain the first dataset in the target site; replicating, from the source site to the target site, the respective components of the first dataset according to the policy from the analyzing, upon detecting inputs enabling the first service, wherein the first service is a disaster recovery service for a database virtual machine of the source site, wherein the first dataset comprises components of a data volume, a log volume, and an index volume of the database virtual machine, wherein the data volume and the log volume are, from the analyzing, respectively determined to be essential for the disaster recovery service and the policy accordingly dictates that the data protection service provider replicates the data volume and the log volume from the source site to the target site, with a highest priority and most frequently, and wherein the index volume is determined to be valuable for the disaster recovery service and the policy accordingly dictates that the data protection service provider does not replicate the index volume from the source site to the target site when the network bandwidth is not available but the data protection service provider reconstructs the index volume by use of a replicated data volume and a replicated log volume at the target site; and performing the disaster recovery service in the target site by use of the replicated data volume, the replicated log volume, and a reconstructed index volume.
 15. The system of claim 14, the analyzing comprising: determining that a first component of the first dataset is essential to the first service based on applying analytics data to the first dataset, the first component being essential indicating that the first component is necessary for the target site to provide the first service, such that the policy is determined for the data protection service provider to replicate the first component with a highest priority and most frequently.
 16. The system of claim 14, the analyzing comprising: determining that a second component of the first dataset is valuable to the first service based on applying analytics data to the first dataset, the second component being valuable indicating that the second component is not necessary but helpful for the target site to provide the first service, such that the policy is determined for the data protection service provider to replicate the second component if the network bandwidth is available.
 17. The system of claim 14, the analyzing comprising: determining that a third component of the first dataset is non-essential to the first service based on applying analytics data to the first dataset, the third component being non-essential indicating that the third component does not contribute to the first service when present at the target site, such that the policy is determined for the data protection service provider not to replicate the third component to the target site. 